Law In Order

Who are Law In Order and what do they do?

Established in 1999, Law In Order is a leading supplier of end to end document and digital solutions for the legal industry. Their expert services add real value to high volume document production, expert eDiscovery management and specialist court services, including eHearings. Their expertise in both traditional and modern technology-based services means they are a highly effective single-source provider for even the most complex of matters. With offices in Brisbane, Sydney, Melbourne, Perth and India, Law In Order are staffed by experienced litigation support professionals 365 days a year, ready to assist at any time. Such easy availability means clients across Australia and around the globe enjoy immediate, unrestricted access to the services they need exactly when they need them.

How does Speechmatics help you differentiate from the competition?

Law In Order transforms voice data to text with machine learning as part of their suite of eDiscovery services. The differentiator is that the data remains in Australia while the voice is converted to text.

Challenge

With rapidly growing demand over the past few years, Slack expanded to serve more global customers, including large-scale enterprises such as Amazon, IBM, and HSBC. To support this growth, Slack needed to enable ACH and credit cards payments globally, automate a custom usage-based invoice per customer that accepts multiple payment methods, let customers adjust billing plans and frequency, and apply proper taxes globally—in short, offer every customer a best-in-class purchasing experience. Slack determined that building its ideal experience in-house would require diverting immense engineering resources away from its core product. Slack Product Manager Britt Jamison found himself asking, “Can we deliver more value to our customers if we let Stripe handle what they're experts at, so we can focus on our core competencies?”

Solution

Slack determined that by partnering with Stripe, which it runs on AWS, it could build the enterprise payments experience its customers required without trading off its other priorities. “The initial launch took about two weeks, and during that time, Stripe’s deployment and support teams acted as our expert advisers,” Jamison said. “We even leveraged a shared Slack channel for assistance, advice, and payments best practices when launching new currencies internationally.” Slack implemented Stripe Payments, Billing, Radar (fraud prevention), and Sigma (SQL reporting). “Having a billing system that lets you stay nimble to respond to customers' needs is really critical. Stripe gives you that flexibility,” said Jackie Rocca, Director of Product.

Results

Slack usage and demand surged during the COVID-19 pandemic, which forced millions to adjust to remote work. Prioritization of internal resources was even more crucial—and so was ensuring a smooth experience for millions of Slack users. During this time, Slack was able to ensure nearly 100% uptime during the heaviest usage period in company history and launch much-needed functionality on its ambitious product roadmap. By letting Stripe handle all things payments, Slack was able to have all engineering resources focused on its core product. Stripe helped Slack set up and optimize payments in 15 countries, implementing local payment methods to increase acceptance rates and maximize Slack's FY20 $630M earnings. Stripe has also helped Slack recoup engineering bandwidth in perpetuity: Sigma provides Slack’s accounting team with reporting to review customer fair billing questions, reducing engineering time spent on customer usage queries.

This enables them to identify opportunities to improve efficiency, reduce customer effort, and continually measure customer experience without needing to manually listen to customer calls or solicit agent/customer self-reporting. These applications integrate proprietary voice analysis technology with Speechmatics’ any-context speech recognition to generate next-level insights from recorded calls. Unlocking the voice data from calls using automatic speech-to-text enables businesses to analyze the data to drive insight and meaning at scale.